3D Point Capsule Networks

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Authors Tolga Birdal, Yongheng Zhao, Federico Tombari, Haowen Deng
Journal/Conference Name CVPR 2019 6
Paper Category
Paper Abstract In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence of our novel unified 3D auto-encoder formulation. Their dynamic routing scheme and the peculiar 2D latent space deployed by our approach bring in improvements for several common point cloud-related tasks, such as object classification, object reconstruction and part segmentation as substantiated by our extensive evaluations. Moreover, it enables new applications such as part interpolation and replacement.
Date of publication 2018
Code Programming Language Multiple
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